20,297 research outputs found
Chaotic Crystallography: How the physics of information reveals structural order in materials
We review recent progress in applying information- and computation-theoretic
measures to describe material structure that transcends previous methods based
on exact geometric symmetries. We discuss the necessary theoretical background
for this new toolset and show how the new techniques detect and describe novel
material properties. We discuss how the approach relates to well known
crystallographic practice and examine how it provides novel interpretations of
familiar structures. Throughout, we concentrate on disordered materials that,
while important, have received less attention both theoretically and
experimentally than those with either periodic or aperiodic order.Comment: 9 pages, two figures, 1 table;
http://csc.ucdavis.edu/~cmg/compmech/pubs/ChemOpinion.ht
Empirical analysis of dynamic load balancing techniques in cloud computing
Virtualization, dispersed registration, systems administration, programming, and web administrations are all examples of distributed computing. Customers, datacenters, and scattered servers are just a few of the components that make up a cloud. It includes things like internal failure adaption, high accessibility, flexibility, adaptability, lower client overhead, lower ownership costs, on-demand advantages, and so on. The basis of a feasible load adjusting computation is key to resolving these challenges. CPU load, memory limit, deferral, and system load are all examples of heaps. Burden adjustment is a method for distributing the load across the many hubs of a conveyance framework in order to optimize asset utilization and employment response time while avoiding a situation where some hubs are heavily loaded while others are idle or performing little work. Burden adjustment ensures that at any one time, each processor in the framework or each hub in the system does about the same amount of work. This method may be initiated by the sender, the collector, or the symmetric sort (the blend of sender-started and recipient started types). With some example data center loads, the goal is to create several dynamic load balancing techniques such as Round Robin, Throttled, Equally Spread Current Execution Load, and Shortest Job First algorithms
Faults and unbalance forces in the switched reluctance machine
The paper identifies and analyzes a number of severe fault conditions that can occur in the switched reluctance machine, from the electrical and mechanical points of view. It is shown how the currents, torques, and forces may be estimated, and examples are included showing the possibility of large lateral forces on the rotor. The methods used for analysis include finite-element analysis, magnetic circuit models, and experiments on a small machine specially modified for the measurement of forces and magnetization characteristics when the rotor is off-center. Also described is a computer program (PC-SRD dynamic) which is used for simulating operation under fault conditions as well as normal conditions. The paper discusses various electrical configurations of windings and controller circuits, along with methods of fault detection and protective relaying. The paper attempts to cover several analytical and experimental aspects as well as methods of detection and protection
Learning Moore Machines from Input-Output Traces
The problem of learning automata from example traces (but no equivalence or
membership queries) is fundamental in automata learning theory and practice. In
this paper we study this problem for finite state machines with inputs and
outputs, and in particular for Moore machines. We develop three algorithms for
solving this problem: (1) the PTAP algorithm, which transforms a set of
input-output traces into an incomplete Moore machine and then completes the
machine with self-loops; (2) the PRPNI algorithm, which uses the well-known
RPNI algorithm for automata learning to learn a product of automata encoding a
Moore machine; and (3) the MooreMI algorithm, which directly learns a Moore
machine using PTAP extended with state merging. We prove that MooreMI has the
fundamental identification in the limit property. We also compare the
algorithms experimentally in terms of the size of the learned machine and
several notions of accuracy, introduced in this paper. Finally, we compare with
OSTIA, an algorithm that learns a more general class of transducers, and find
that OSTIA generally does not learn a Moore machine, even when fed with a
characteristic sample
Mathematical practice, crowdsourcing, and social machines
The highest level of mathematics has traditionally been seen as a solitary
endeavour, to produce a proof for review and acceptance by research peers.
Mathematics is now at a remarkable inflexion point, with new technology
radically extending the power and limits of individuals. Crowdsourcing pulls
together diverse experts to solve problems; symbolic computation tackles huge
routine calculations; and computers check proofs too long and complicated for
humans to comprehend.
Mathematical practice is an emerging interdisciplinary field which draws on
philosophy and social science to understand how mathematics is produced. Online
mathematical activity provides a novel and rich source of data for empirical
investigation of mathematical practice - for example the community question
answering system {\it mathoverflow} contains around 40,000 mathematical
conversations, and {\it polymath} collaborations provide transcripts of the
process of discovering proofs. Our preliminary investigations have demonstrated
the importance of "soft" aspects such as analogy and creativity, alongside
deduction and proof, in the production of mathematics, and have given us new
ways to think about the roles of people and machines in creating new
mathematical knowledge. We discuss further investigation of these resources and
what it might reveal.
Crowdsourced mathematical activity is an example of a "social machine", a new
paradigm, identified by Berners-Lee, for viewing a combination of people and
computers as a single problem-solving entity, and the subject of major
international research endeavours. We outline a future research agenda for
mathematics social machines, a combination of people, computers, and
mathematical archives to create and apply mathematics, with the potential to
change the way people do mathematics, and to transform the reach, pace, and
impact of mathematics research.Comment: To appear, Springer LNCS, Proceedings of Conferences on Intelligent
Computer Mathematics, CICM 2013, July 2013 Bath, U
Performance estimation of interior permanent-magnet brushless motors using the voltage-driven flux-MMF diagram
The flux-magnetomotive force (flux-MMF) diagram, or "energy conversion loop," is a powerful tool for computing the parameters of saturated interior permanent-magnet brushless motors, especially when the assumptions underlying classical dq theory are not valid, as is often the case in modern practice. Efficient finite-element computation of the flux-MMF diagram is possible when the motor current is known a priori, but in high-speed operation the current regulator can lose control of the current waveform and the computation becomes "voltage-driven" rather than "current-driven." This paper describes an efficient method for estimating the motor performance-average torque, inductances-by solving the voltage-driven problem. It presents experimental validation for a two-pole brushless interior permanent-magnet motor. The paper also discusses the general conditions under which this method is appropriate, and compares the method with alternative approaches
Deep Learning: Our Miraculous Year 1990-1991
In 2020, we will celebrate that many of the basic ideas behind the deep
learning revolution were published three decades ago within fewer than 12
months in our "Annus Mirabilis" or "Miraculous Year" 1990-1991 at TU Munich.
Back then, few people were interested, but a quarter century later, neural
networks based on these ideas were on over 3 billion devices such as
smartphones, and used many billions of times per day, consuming a significant
fraction of the world's compute.Comment: 37 pages, 188 references, based on work of 4 Oct 201
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